#!/usr/bin/env python

#MIT License
#Copyright (c) 2017 Massimiliano Patacchiola
#
#Permission is hereby granted, free of charge, to any person obtaining a copy
#of this software and associated documentation files (the "Software"), to deal
#in the Software without restriction, including without limitation the rights
#to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
#copies of the Software, and to permit persons to whom the Software is
#furnished to do so, subject to the following conditions:
#
#The above copyright notice and this permission notice shall be included in all
#copies or substantial portions of the Software.
#
#THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
#IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
#FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
#AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
#LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
#OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
#SOFTWARE.

import numpy as np

#Trowing a dice for N times and evaluating the expectation
dice = np.random.randint(low=1, high=7, size=3)
print("Expectation (3 times): " + str(np.mean(dice)))
dice = np.random.randint(low=1, high=7, size=10)
print("Expectation (10 times): " + str(np.mean(dice)))
dice = np.random.randint(low=1, high=7, size=100)
print("Expectation (100 times): " + str(np.mean(dice)))
dice = np.random.randint(low=1, high=7, size=1000)
print("Expectation (1000 times): " + str(np.mean(dice)))
dice = np.random.randint(low=1, high=7, size=100000)
print("Expectation (100000 times): " + str(np.mean(dice)))
